King's College London

Research portal

Genomic influences on self-reported childhood maltreatment

Research output: Contribution to journalArticle

Shareefa Dalvie, Adam X. Maihofer, Jonathan R.I. Coleman, Bekh Bradley, Gerome Breen, Leslie A. Brick, Chia Yen Chen, Karmel W. Choi, Laramie E. Duncan, Guia Guffanti, Magali Haas, Supriya Harnal, Israel Liberzon, Nicole R. Nugent, Allison C. Provost, Kerry J. Ressler, Katy Torres, Ananda B. Amstadter, S. Bryn Austin, Dewleen G. Baker & 46 more Elizabeth A. Bolger, Richard A. Bryant, Joseph R. Calabrese, Douglas L. Delahanty, Lindsay A. Farrer, Norah C. Feeny, Janine D. Flory, David Forbes, Sandro Galea, Aarti Gautam, Joel Gelernter, Rasha Hammamieh, Marti Jett, Angela G. Junglen, Milissa L. Kaufman, Ronald C. Kessler, Alaptagin Khan, Henry R. Kranzler, Lauren A.M. Lebois, Charles Marmar, Matig R. Mavissakalian, Alexander McFarlane, Meaghan O’ Donnell, Holly K. Orcutt, Robert H. Pietrzak, Victoria B. Risbrough, Andrea L. Roberts, Alex O. Rothbaum, Peter Roy-Byrne, Ken Ruggiero, Antonia V. Seligowski, Christina M. Sheerin, Derrick Silove, Jordan W. Smoller, Murray B. Stein, Martin H. Teicher, Robert J. Ursano, Miranda Van Hooff, Sherry Winternitz, Jonathan D. Wolff, Rachel Yehuda, Hongyu Zhao, Lori A. Zoellner, Dan J. Stein, Karestan C. Koenen, Caroline M. Nievergelt

Original languageEnglish
Article number38
JournalTranslational psychiatry
Volume10
Issue number1
DOIs
Publication statusPublished - 1 Dec 2020

King's Authors

Abstract

Childhood maltreatment is highly prevalent and serves as a risk factor for mental and physical disorders. Self-reported childhood maltreatment appears heritable, but the specific genetic influences on this phenotype are largely unknown. The aims of this study were to (1) identify genetic variation associated with self-reported childhood maltreatment, (2) estimate SNP-based heritability (h2 snp), (3) assess predictive value of polygenic risk scores (PRS) for childhood maltreatment, and (4) quantify genetic overlap of childhood maltreatment with mental and physical health-related phenotypes, and condition the top hits from our analyses when such overlap is present. Genome-wide association analysis for childhood maltreatment was undertaken, using a discovery sample from the UK Biobank (UKBB) (n = 124,000) and a replication sample from the Psychiatric Genomics Consortium-posttraumatic stress disorder group (PGC-PTSD) (n = 26,290). h2 snp for childhood maltreatment and genetic correlations with mental/physical health traits were calculated using linkage disequilibrium score regression. PRS was calculated using PRSice and mtCOJO was used to perform conditional analysis. Two genome-wide significant loci associated with childhood maltreatment (rs142346759, p = 4.35 × 10−8, FOXP1; rs10262462, p = 3.24 × 10−8, FOXP2) were identified in the discovery dataset but were not replicated in PGC-PTSD. h2 snp for childhood maltreatment was ~6% and the PRS derived from the UKBB was significantly predictive of childhood maltreatment in PGC-PTSD (r2 = 0.0025; p = 1.8 × 10−15). The most significant genetic correlation of childhood maltreatment was with depressive symptoms (rg = 0.70, p = 4.65 × 10−40), although we show evidence that our top hits may be specific to childhood maltreatment. This is the first large-scale genetic study to identify specific variants associated with self-reported childhood maltreatment. Speculatively, FOXP genes might influence externalizing traits and so be relevant to childhood maltreatment. Alternatively, these variants may be associated with a greater likelihood of reporting maltreatment. A clearer understanding of the genetic relationships of childhood maltreatment, including particular abuse subtypes, with a range of phenotypes, may ultimately be useful in in developing targeted treatment and prevention strategies.

View graph of relations

© 2018 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454